Non-Destructive Prediction of Moisture Content and Freezable Water Content of Purple-Fleshed Sweet Potato Slices during Drying Process Using Hyperspectral Imaging Technique

2016 ◽  
Vol 10 (5) ◽  
pp. 1535-1546 ◽  
Author(s):  
Yue Sun ◽  
Yunhong Liu ◽  
Huichun Yu ◽  
Anguo Xie ◽  
Xin Li ◽  
...  
Keyword(s):  
Moisture Content ◽  
Water Content ◽  
Sweet Potato ◽  
Hyperspectral Imaging ◽  
Imaging Technique ◽  
Drying Process ◽  
Freezable Water ◽  
Non Destructive ◽  
Potato Slices

scholarly journals Prediction of moisture content uniformity using hyperspectral imaging technology during the drying of maize kernel

2015 ◽  
Vol 29 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Min Huang ◽  
Weiyan Zhao ◽  
Qingguo Wang ◽  
Min Zhang ◽  
Qibing Zhu
Keyword(s):  
Moisture Content ◽  
Hyperspectral Imaging ◽  
Imaging Technique ◽  
Direct Method ◽  
Correlation Coefficients ◽  
Critical Parameters ◽  
Content Uniformity ◽  
Least Squares Regression ◽  
Drying Process ◽  
Maize Kernels

Abstract Moisture content uniformity is one of critical parameters to evaluate the quality of dried products and the drying technique. The potential of the hyperspectral imaging technique for evaluating the moisture content uniformity of maize kernels during the drying process was investigated. Predicting models were established using the partial least squares regression method. Two methods, using the prediction value of moisture content to calculate the uniformity (indirect) and predicting the moisture content uniformity directly, were investigated. Better prediction results were achieved using the direct method (with correlation coefficients RP = 0.848 and root-mean-square error of prediction RMSEP = 2.73) than the indirect method (RP = 0.521 and RMSEP = 10.96). The hyperspectral imaging technique showed significant potential in evaluating moisture content uniformity of maize kernels during the drying process.

scholarly journals KARAKTERISTIK SIFAT-SIFAT KIMIA DAN ORGANOLEPTIK KUE KERING BERBAHAN DASAR PATI SAGU, UBI KAYU, UBI JALAR DAN KELADI

2016 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Febby J Polnaya ◽  
Rachel Breemer
Keyword(s):  
Moisture Content ◽  
Water Content ◽  
Sweet Potato ◽  
Sensory Analysis ◽  
Total Protein ◽  
Proximate Composition ◽  
Ash Content ◽  
Crude Fiber ◽  
Brownish Yellow ◽  
Color Texture

The purpose of this research was to characterize chemical and sensory properties (color, texture, taste and liking) of starch-based sago, cassava, sweet potato and cocoyam cookies. Analysis of cookies include moisture content, ash, fat, protein, crude fiber and sensory analysis including color, texture, taste and likeness). The proximate composition indicated that the water content of cookies varied between 1.48 to 2.05%, ash content of 0.65 to 0.72%, 19.23 to 21.76% of fat, crude fiber from 0.41 to 0.71% and 1.33 to 2.42% of total protein. Based on organoleptic tests, the color of cookies was yellow to brownish-yellow, with crispy texture, the taste was sweet and were mostly preferred.

HYPERSPECTRAL IMAGING TECHNIQUE AS A STATE OF ART TECHNOLOGY IN MEAT SCIENCE

2016 ◽  
Vol 2 (3) ◽  
pp. 127-137
Author(s):  
Hasan Ibrahim Kozan ◽  
Cemalettin Sariçoban ◽  
Hasan Ali Akyürek ◽  
Ahmet Ünver
Keyword(s):  
Meat Quality ◽  
Hyperspectral Imaging ◽  
Imaging Technique ◽  
Saturated Fat ◽  
Cholesterol Content ◽  
Quality Parameters ◽  
Meat Industry ◽  
Meat Safety ◽  
Non Destructive ◽  
Day By Day

Nowadays, the concern of meat consumption, safety and quality has been popular due to some health risks such coronary heart disease, stroke and diabetes caused by the content as saturated fat, cholesterol content and carcinogenic compounds, for consumers. The importance of the need of new non-destructive and fast meat analyze methods are increasing day by day.  For this, researchers have developed some methods to objectively measure the meat quality and meat safety as well as illness sources. Hyperspectral imaging technique is one of the most popular technology which combines imaging and spectroscopic technology. This technique is a non-destructive, real-time and easy-to-use detection tool for meat quality and safety assessment. It is possible to determine chemical structure and related physical properties of meat.It is clear that hyperspectral imaging technology can be automated for manufacturing in meat industry and all of data’s obtained from the hyperspectral images which represents the chemical quality parameters of meats in the process can be saved to database. 

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